Marketing is the art of reaching the right customer or consumer, with the right message at the right time. Since marketers cannot afford to craft unique messages for each targeted individual, they always deal with large segments of their target market at any given time.
An efficient system of targeting advertisements can improve a marketer's return on the advertising budget. However, the learning curve in determining such targeting parameters for any given product or brand is expensive and time consuming. If the marketers have a history of targeting actions, they can analyze the previous results to determine which permutations of targeting criteria have worked in the past. Otherwise, the marketers may be unable to predict if the price premium is worth paying for a certain set of targeting criteria. Moreover, an exclusive focus on targeting criteria of past campaigns may lead to reinforcement of inefficient choices.
Thus, what is needed is a system and method to identify targeting criteria for online advertising campaigns based on natural query event data in order to improve the overall effectiveness of the advertisements.